Noah Iliinsky: Tech Talk on Designing Data Visualizations

Note: This post was written by Yael Garten, a Senior Data Scientist at LinkedIn. Yael joined Linkedin in 2011, where she leads our mobile analytics team. She previously worked at Stanford on text mining, personalized medicine, and biomedical informatics.

We live in an era of Big Data. But how do we use all of that data to answer questions and communicate those answers effectively?

Earlier this month, we hosted Noah at LinkedIn to give a tech talk on “Designing Effective Data Visualizations“. We are proud to make these tech talks open to the public, and enjoyed a great mix of attendees from local companies and universities. If you couldn’t attend the talk in person or remotely, I encourage you to watch the recording, embedded above.

Why do we visualize data? As Noah tells us, visualization makes data accessible. It gives us faster access to actionable insights and allows access to huge amounts of data. Visualization enables both data exploration (when you are still trying to discover the story) and data explanation (when you have a story to tell). Noah reviewed some great examples (watch the talk!), with an emphasis on the dos and don’ts of data visualization.

In particular, he provided a step-by-step framework for traversing the path from question to answer:

Phase 1: Decide what to visualize.

Understand the question your audience wants to answer.

Understand the actions they are hoping the answer will drive.

Consider who is consuming this data — their needs, biases, etc.

Decide what data to use — and what data not to use — and what relationships you are interested in.

You are not your audience. This is a huge lesson that all of us must internalize to be great at what we do. Consider what you need to communicate to marketers, investors, member of the general public, etc.